Polygenic contributions to performance on the Balloon Analogue Risk Task.

Risky decision-making is a common, heritable endophenotype seen across many psychiatric disorders. Its underlying genetic architecture is incompletely explored. We examined behavior in the Balloon Analogue Risk Task (BART), which tests risky decision-making, in two independent samples of European ancestry. One sample (n = 1138) comprised healthy participants and some psychiatric patients (53 schizophrenia, 42 bipolar disorder, 47 ADHD); the other (n = 911) excluded for recent treatment of various psychiatric disorders but not ADHD. Participants provided DNA and performed the BART, indexed by mean adjusted pumps. We constructed a polygenic risk score (PRS) for discovery in each dataset and tested it in the other as replication. Subsequently, a genome-wide MEGA-analysis, combining both samples, tested genetic correlation with risk-taking self-report in the UK Biobank sample and psychiatric phenotypes characterized by risk-taking (ADHD, Bipolar Disorder, Alcohol Use Disorder, prior cannabis use) in the Psychiatric Genomics Consortium. The PRS for BART performance in one dataset predicted task performance in the replication sample (r = 0.13, p = 0.000012, pFDR = 0.000052), as did the reciprocal analysis (r = 0.09, p = 0.0083, pFDR=0.04). Excluding participants with psychiatric diagnoses produced similar results. The MEGA-GWAS identified a single SNP (rs12023073; p = 3.24 × 10-8) near IGSF21, a protein involved in inhibitory brain synapses; replication samples are needed to validate this result. A PRS for self-reported cannabis use (p = 0.00047, pFDR = 0.0053), but not self-reported risk-taking or psychiatric disorder status, predicted behavior on the BART in our MEGA-GWAS sample. The findings reveal polygenic architecture of risky decision-making as measured by the BART and highlight its overlap with cannabis use.

Childhood trauma and cognitive functioning in individuals at clinical high risk (CHR) for psychosis.

Evidence suggests that early trauma may have a negative effect on cognitive functioning in individuals with psychosis, yet the relationship between childhood trauma and cognition among those at clinical high risk (CHR) for psychosis remains unexplored. Our sample consisted of 626 CHR children and 279 healthy controls who were recruited as part of the North American Prodrome Longitudinal Study 2. Childhood trauma up to the age of 16 (psychological, physical, and sexual abuse, emotional neglect, and bullying) was assessed by using the Childhood Trauma and Abuse Scale. Multiple domains of cognition were measured at baseline and at the time of psychosis conversion, using standardized assessments. In the CHR group, there was a trend for better performance in individuals who reported a history of multiple types of childhood trauma compared with those with no/one type of trauma (Cohen d = 0.16). A history of multiple trauma types was not associated with greater cognitive change in CHR converters over time. Our findings tentatively suggest there may be different mechanisms that lead to CHR states. Individuals who are at clinical high risk who have experienced multiple types of childhood trauma may have more typically developing premorbid cognitive functioning than those who reported minimal trauma do. Further research is needed to unravel the complexity of factors underlying the development of at-risk states.

Persistent negative symptoms in youth at clinical high risk for psychosis: A longitudinal study.

BACKGROUND: Severity of negative symptoms has been associated with poor functioning, cognitive deficits, and defeatist beliefs in schizophrenia patients. However, one area that remains understudied is persistent negative symptoms (PNS). Negative symptoms, including PNS, have been observed in those at clinical high-risk (CHR) for psychosis. The aim of this study was to determine if PNS were associated with functioning, neurocognition, and defeatist beliefs in a CHR sample. METHOD: CHR participants (n = 764) were recruited for the North American Prodrome Longitudinal Study. Negative symptoms were rated on the Scale of Psychosis-risk Symptoms. Generalized linear mixed models for repeated measures were used to examine changes over time between and within groups (PNS vs non-PNS). RESULTS: The PNS group (n = 67) had significant deficits in functioning at baseline, 6, 12, 18, and 24-months compared to the non-PNS group (n = 673). Functioning improved over time in the non-PNS group, while functioning in the PNS group remained relatively stable and poor over a two-year period. A consistent trend emerged demonstrating higher defeatist beliefs in the PNS group; however, this result was lost when controlling for persistent depressive symptoms. There were no significant differences between the groups on neurocognition, social cognition, and transition to psychosis. CONCLUSIONS: PNS exist in youth at CHR for psychosis, resulting in significant and persistent functional impairment, which remains when controlling for persistent depressive symptoms. PNS remain even in CHR youth who do not transition to psychosis. Thus, PNS may represent an unmet therapeutic need in CHR populations for which there are currently no effective treatments.

Longitudinal changes in social cognition in individuals at clinical high risk for psychosis: An outcome based analysis.

Social cognition deficits have been observed in individuals at clinical high risk (CHR) for psychosis. Longitudinal change in social cognition were analyzed in CHR individuals from the North American Prodrome Longitudinal Study (NAPLS2) based on outcome at 24 months. Individuals (n = 359) were classified into remission, symptomatic, prodromal progression and transition to psychosis (CHR-T) groups. Social cognition was assessed using theory of mind, emotion perception, and social perception tasks. There were no differences at baseline or 24 months between the groups on social cognition. Non-transition groups improved significantly over time on social cognition, but CHR-T did not show this effect.

GWAS meta-analysis reveals novel loci and genetic correlates for general cognitive function: a report from the COGENT consortium.

This corrects the article DOI: 10.1038/mp.2016.244.

Neuregulin signaling pathway in smoking behavior.

Understanding molecular processes that link comorbid traits such as addictions and mental disorders can provide novel therapeutic targets. Neuregulin signaling pathway (NSP) has previously been implicated in schizophrenia, a neurodevelopmental disorder with high comorbidity to smoking. Using a Finnish twin family sample, we have previously detected association between nicotine dependence and ERBB4 (a neuregulin receptor), and linkage for smoking initiation at the ERBB4 locus on 2q33. Further, Neuregulin3 has recently been shown to associate with nicotine withdrawal in a behavioral mouse model. In this study, we scrutinized association and linkage between 15 036 common, low frequency and rare genetic variants in 10 NSP genes and phenotypes encompassing smoking and alcohol use. Using the Finnish twin family sample (N=1998 from 740 families), we detected 66 variants (representing 23 LD blocks) significantly associated (false discovery rate P<0.05) with smoking initiation, nicotine dependence and nicotine withdrawal. We comprehensively annotated the associated variants using expression (eQTL) and methylation quantitative trait loci (meQTL) analyses in a Finnish population sample. Among the 66 variants, we identified 25 eQTLs (in NRG1 and ERBB4), 22 meQTLs (in NRG3, ERBB4 and PSENEN), a missense variant in NRG1 (rs113317778) and a splicing disruption variant in ERBB4 (rs13385826). Majority of the QTLs in blood were replicated in silico using publicly available databases, with additional QTLs observed in brain. In conclusion, our results support the involvement of NSP in smoking behavior but not in alcohol use and abuse, and disclose functional potential for 56 of the 66 associated single-nucleotide polymorphism.

GWAS meta-analysis reveals novel loci and genetic correlates for general cognitive function: a report from the COGENT consortium.

The complex nature of human cognition has resulted in cognitive genomics lagging behind many other fields in terms of gene discovery using genome-wide association study (GWAS) methods. In an attempt to overcome these barriers, the current study utilized GWAS meta-analysis to examine the association of common genetic variation (~8M single-nucleotide polymorphisms (SNP) with minor allele frequency ⩾1%) to general cognitive function in a sample of 35 298 healthy individuals of European ancestry across 24 cohorts in the Cognitive Genomics Consortium (COGENT). In addition, we utilized individual SNP lookups and polygenic score analyses to identify genetic overlap with other relevant neurobehavioral phenotypes. Our primary GWAS meta-analysis identified two novel SNP loci (top SNPs: rs76114856 in the CENPO gene on chromosome 2 and rs6669072 near LOC105378853 on chromosome 1) associated with cognitive performance at the genome-wide significance level (P<5 × 10-8). Gene-based analysis identified an additional three Bonferroni-corrected significant loci at chromosomes 17q21.31, 17p13.1 and 1p13.3. Altogether, common variation across the genome resulted in a conservatively estimated SNP heritability of 21.5% (s.e.=0.01%) for general cognitive function. Integration with prior GWAS of cognitive performance and educational attainment yielded several additional significant loci. Finally, we found robust polygenic correlations between cognitive performance and educational attainment, several psychiatric disorders, birth length/weight and smoking behavior, as well as a novel genetic association to the personality trait of openness. These data provide new insight into the genetics of neurocognitive function with relevance to understanding the pathophysiology of neuropsychiatric illness.

Insights into psychosis risk from leukocyte microRNA expression.

Dysregulation of immune system functions has been implicated in schizophrenia, suggesting that immune cells may be involved in the development of the disorder. With the goal of a biomarker assay for psychosis risk, we performed small RNA sequencing on RNA isolated from circulating immune cells. We compared baseline microRNA (miRNA) expression for persons who were unaffected (n=27) or who, over a subsequent 2-year period, were at clinical high risk but did not progress to psychosis (n=37), or were at high risk and did progress to psychosis (n=30). A greedy algorithm process led to selection of five miRNAs that when summed with +1 weights distinguished progressed from nonprogressed subjects with an area under the receiver operating characteristic curve of 0.86. Of the five, miR-941 is human-specific with incompletely understood functions, but the other four are prominent in multiple immune system pathways. Three of those four are downregulated in progressed vs. nonprogressed subjects (with weight -1 in a classifier function that increases with risk); all three have also been independently reported as downregulated in monocytes from schizophrenia patients vs. unaffected subjects. Importantly, these findings passed stringent randomization tests that minimized the risk of conclusions arising by chance. Regarding miRNA-miRNA correlations over the three groups, progressed subjects were found to have much weaker miRNA orchestration than nonprogressed or unaffected subjects. If independently verified, the leukocytic miRNA biomarker assay might improve accuracy of psychosis high-risk assessments and eventually help rationalize preventative intervention decisions.

A phenome-wide examination of neural and cognitive function.

This data descriptor outlines a shared neuroimaging dataset from the UCLA Consortium for Neuropsychiatric Phenomics, which focused on understanding the dimensional structure of memory and cognitive control (response inhibition) functions in both healthy individuals (130 subjects) and individuals with neuropsychiatric disorders including schizophrenia (50 subjects), bipolar disorder (49 subjects), and attention deficit/hyperactivity disorder (43 subjects). The dataset includes an extensive set of task-based fMRI assessments, resting fMRI, structural MRI, and high angular resolution diffusion MRI. The dataset is shared through the OpenfMRI project, and is formatted according to the Brain Imaging Data Structure (BIDS) standard.

Multidimensional assessment of impulsivity in schizophrenia, bipolar disorder, and major depressive disorder: testing for shared endophenotypes.

BACKGROUND: Impulsivity is associated with bipolar disorder as a clinical feature during and between manic episodes and is considered a potential endophenotype for the disorder. Schizophrenia and major depressive disorder share substantial genetic overlap with bipolar disorder, and these two disorders have also been associated with elevations in impulsivity. However, little is known about the degree of overlap among these disorders in discrete subfacets of impulsivity and whether any overlap is purely phenotypic or due to shared genetic diathesis. METHOD: We focused on five subfacets of impulsivity: self-reported attentional, motor, and non-planning impulsivity, self-reported sensation seeking, and a behavioral measure of motor inhibition (stop signal reaction time; SSRT). We examined these facets within and across disorder proband and co-twin groups, modeled heritability, and tested for endophenotypic patterning in a sample of twin pairs recruited from the Swedish Twin Registry (N = 420). RESULTS: We found evidence of moderate to high levels of heritability for all five subfacets. All three proband groups and their unaffected co-twins showed elevations on attentional, motor, and non-planning impulsivity. Schizophrenia probands (but not their co-twins) showed significantly lower sensation seeking, and schizophrenia and bipolar disorder probands (but not in their co-twins) had significantly longer SSRTs, compared with healthy controls and the other groups. CONCLUSIONS: Attentional, motor, and non-planning impulsivity emerged as potential shared endophenotypes for the three disorders, whereas sensation seeking and SSRT were associated with phenotypic affection but not genetic loading for these disorders.

Substance use in individuals at clinical high risk of psychosis.

BACKGROUND: A series of research reports has indicated that the use of substances such as cannabis, alcohol and tobacco are higher in youth at clinical high risk (CHR) of developing psychosis than in controls. Little is known about the longitudinal trajectory of substance use, and findings on the relationship between substance use and later transition to psychosis in CHR individuals are mixed. METHOD: At baseline and 6- and 12-month follow-ups, 735 CHR and 278 control participants completed the Alcohol and Drug Use Scale and a cannabis use questionnaire. The longitudinal trajectory of substance use was evaluated with linear mixed models. RESULTS: CHR participants endorsed significantly higher cannabis and tobacco use severity, and lower alcohol use severity, at baseline and over a 1-year period compared with controls. CHR youth had higher lifetime prevalence and frequency of cannabis, and were significantly younger upon first use, and were more likely to use alone and during the day. Baseline substance use did not differentiate participants who later transitioned to psychosis (n = 90) from those who did not transition (n = 272). Controls had lower tobacco use than CHR participants with a prodromal progression clinical outcome and lower cannabis use than those with a psychotic clinical outcome at the 2-year assessment. CONCLUSIONS: In CHR individuals cannabis and tobacco use is higher than in controls and this pattern persists across 1 year. Evaluation of clinical outcome may provide additional information on the longitudinal impact of substance use that cannot be detected through evaluation of transition/non-transition to psychosis alone.

Alcohol confounds relationship between cannabis misuse and psychosis conversion in a high-risk sample.

OBJECTIVE: Cannabis use has been examined as a predictor of psychosis in clinical high-risk (CHR) samples, but little is known about the impact of other substances on this relationship. METHOD: Substance use was assessed in a large sample of CHR participants (N = 370, mean age = 18.3) enrolled in the multisite North American Prodrome Longitudinal Study Phase 1 project. Three hundred and forty-one participants with cannabis use data were divided into groups: No Use (NU, N = 211); Cannabis Use without impairment (CU, N = 63); Cannabis Abuse/Dependence (CA/CD, N = 67). Participants (N = 283) were followed for ≥2 years to determine psychosis conversion. RESULTS: Alcohol (45.3%) and cannabis (38.1%) were the most common substances. Cannabis use groups did not differ on baseline attenuated positive symptoms. Seventy-nine of 283 participants with cannabis and follow-up data converted to psychosis. Survival analysis revealed significant differences between conversion rates in the CA/CD group compared with the No Use (P = 0.031) and CU group (P = 0.027). CA/CD also significantly predicted psychosis in a regression analysis, but adjusting for alcohol use weakened this relationship. CONCLUSION: The cannabis misuse and psychosis association was confounded by alcohol use. Non-impairing cannabis use was not related to psychosis. Results highlight the need to control for other substance use, so as to not overstate the cannabis/psychosis connection.

Reciprocal causation models of cognitive vs volumetric cerebral intermediate phenotypes for schizophrenia in a pan-European twin cohort.

In aetiologically complex illnesses such as schizophrenia, there is no direct link between genotype and phenotype. Intermediate phenotypes could help clarify the underlying biology and assist in the hunt for genetic vulnerability variants. We have previously shown that cognition shares substantial genetic variance with schizophrenia; however, it is unknown if this reflects pleiotropic effects, direct causality or some shared third factor that links both, for example, brain volume (BV) changes. We quantified the degree of net genetic overlap and tested the direction of causation between schizophrenia liability, brain structure and cognition in a pan-European schizophrenia twin cohort consisting of 1243 members from 626 pairs. Cognitive deficits lie upstream of the liability for schizophrenia with about a quarter of the variance in liability to schizophrenia explained by variation in cognitive function. BV changes lay downstream of schizophrenia liability, with 4% of BV variation explained directly by variation in liability. However, our power to determine the nature of the relationship between BV deviation and schizophrenia liability was more limited. Thus, while there was strong evidence that cognitive impairment is causal to schizophrenia liability, we are not in a position to make a similar statement about the relationship between liability and BV. This is the first study to demonstrate that schizophrenia liability is expressed partially through cognitive deficits. One prediction of the finding that BV changes lie downstream of the disease liability is that the risk loci that influence schizophrenia liability will thereafter influence BV and to a lesser extent. By way of contrast, cognitive function lies upstream of schizophrenia, thus the relevant loci will actually have a larger effect size on cognitive function than on schizophrenia. These are testable predictions.

Proton MRS in twin pairs discordant for schizophrenia.

Proton magnetic resonance spectroscopy ((1)H MRS) neurometabolite abnormalities have been detected widely in subjects with and at risk for schizophrenia. We hypothesized that such abnormalities would be present both in patients with schizophrenia and in their unaffected twin siblings. We acquired magnetic resonance spectra (TR/TE=3000/30 ms) at voxels in the mesial prefrontal gray matter, left prefrontal white matter and left hippocampus in 14 twin pairs discordant for schizophrenia (2 monozygotic, 12 dizygotic), 13 healthy twin pairs (4 monozygotic, 9 dizygotic) and 1 additional unaffected co-twin of a schizophrenia proband. In the mesial prefrontal gray matter voxel, N-acetylaspartate (NAA), creatine+phosphocreatine (Cr), glycerophosphocholine+phosphocholine (Cho) and myo-inositol (mI) did not differ significantly between patients with schizophrenia, their unaffected co-twins or healthy controls. However, glutamate (Glu) was significantly lower in patients with schizophrenia (31%, percent difference) and unaffected co-twins (21%) than in healthy controls (collapsed across twin pairs). In the left hippocampus voxel, levels of NAA (23%), Cr (22%) and Cho (36%) were higher in schizophrenia patients compared with controls. Hippocampal NAA (25%), Cr (22%) and Cho (37%) were also significantly higher in patients than in their unaffected co-twins. Region-to-region differences in metabolite levels were also notable within all three diagnosis groups. These findings suggest that (1)H MRS neurometabolite abnormalities are present not only in patients with schizophrenia, but also in their unaffected co-twins. Thus, reduced mesial prefrontal cortical Glu and elevated hippocampal NAA, Cr and Cho may represent trait markers of schizophrenia risk and, when exacerbated, state markers of schizophrenia itself.

Challenges in phenotype definition in the whole-genome era: multivariate models of memory and intelligence.

Refining phenotypes for the study of neuropsychiatric disorders is of paramount importance in neuroscience. Poor phenotype definition provides the greatest obstacle for making progress in disorders like schizophrenia, bipolar disorder, Attention Deficit/Hyperactivity Disorder (ADHD), and autism. Using freely available informatics tools developed by the Consortium for Neuropsychiatric Phenomics (CNP), we provide a framework for defining and refining latent constructs used in neuroscience research and then apply this strategy to review known genetic contributions to memory and intelligence in healthy individuals. This approach can help us begin to build multi-level phenotype models that express the interactions between constructs necessary to understand complex neuropsychiatric diseases. These results are available online through the http://www.phenowiki.org database. Further work needs to be done in order to provide consensus-building applications for the broadly defined constructs used in neuroscience research.

Phenomics: the systematic study of phenotypes on a genome-wide scale.

Phenomics is an emerging transdiscipline dedicated to the systematic study of phenotypes on a genome-wide scale. New methods for high-throughput genotyping have changed the priority for biomedical research to phenotyping, but the human phenome is vast and its dimensionality remains unknown. Phenomics research strategies capable of linking genetic variation to public health concerns need to prioritize development of mechanistic frameworks that relate neural systems functioning to human behavior. New approaches to phenotype definition will benefit from crossing neuropsychiatric syndromal boundaries, and defining phenotypic features across multiple levels of expression from proteome to syndrome. The demand for high throughput phenotyping may stimulate a migration from conventional laboratory to web-based assessment of behavior, and this offers the promise of dynamic phenotyping-the iterative refinement of phenotype assays based on prior genotype-phenotype associations. Phenotypes that can be studied across species may provide greatest traction, particularly given rapid development in transgenic modeling. Phenomics research demands vertically integrated research teams, novel analytic strategies and informatics infrastructure to help manage complexity. The Consortium for Neuropsychiatric Phenomics at UCLA has been supported by the National Institutes of Health Roadmap Initiative to illustrate these principles, and is developing applications that may help investigators assemble, visualize, and ultimately test multi-level phenomics hypotheses. As the transdiscipline of phenomics matures, and work is extended to large-scale international collaborations, there is promise that systematic new knowledge bases will help fulfill the promise of personalized medicine and the rational diagnosis and treatment of neuropsychiatric syndromes.

Brain surface contraction mapped in first-episode schizophrenia: a longitudinal magnetic resonance imaging study.

Schizophrenia is associated with structural brain abnormalities, but the timing of onset and course of these changes remains unclear. Longitudinal magnetic resonance imaging (MRI) studies have demonstrated progressive brain volume decreases in patients around and after the onset of illness, although considerable discrepancies exist regarding which brain regions are affected. The anatomical pattern of these progressive changes in schizophrenia is largely unknown. In this study, MRI scans were acquired repeatedly from 16 schizophrenia patients approximately 2 years apart following their first episode of illness, and also from 14 age-matched healthy subjects. Cortical Pattern Matching, in combination with Structural Image Evaluation, using Normalisation, of Atrophy, was applied to compare the rates of cortical surface contraction between patients and controls. Surface contraction in the dorsal surfaces of the frontal lobe was significantly greater in patients with first-episode schizophrenia (FESZ) compared with healthy controls. Overall, brain surface contraction in patients and healthy controls showed similar anatomical patterns, with that of the former group exaggerated in magnitude across the entire brain surface. That the pattern of structural change in the early course of schizophrenia corresponds so closely to that associated with normal development is consistent with the hypothesis that a schizophrenia-related factor interacts with normal adolescent brain developmental processes in the pathophysiology of schizophrenia. The exaggerated progressive changes seen in patients with schizophrenia may reflect an increased rate of synaptic pruning, resulting in excessive loss of neuronal connectivity, as predicted by the late neurodevelopmental hypothesis of the illness.

Infant motor development is associated with adult cognitive categorisation in a longitudinal birth cohort study.

BACKGROUND: The relationship between the age of reaching infant developmental milestones and later intellectual function within the normal population remains unresolved. We hypothesised that the age of learning to stand in infancy would be associated with adult executive function and that the association would be apparent throughout the range of abilities, rather than confined to extremes. METHODS: The Northern Finland 1966 Birth Cohort is based upon 12,058 live-born children in a geographic and temporally defined population. Information on age at learning to stand without support was obtained at one year. At age 33-35 a random sample of 104 subjects underwent a neuropsychological test battery including tests of executive function (cognitive categorisation), visuo-spatial memory, verbal learning and visual object learning. We investigated associations between developmental data and adult neuropsychological test scores. RESULTS: There was a significant linear relationship between age of learning to stand and adult categorisation: the earlier the attainment of the milestone, the better was the categorisation. No such relationships were observed between infant neurodevelopment and adult cognition in other neuropsychological domains. CONCLUSION: Even within the normal range of development, early development in the gross motor domain is associated with better adult executive function (in tests of categorisation). Investigation of the determinants and sequelae of normal neural development will facilitate research into a variety of neurodevelopmental disorders.